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In a year, weather can impose storm damage to a home. From year to year the damage is random. Let Y be the dollar value of damage in a given year. Assume that 95% of the year's Y=$1,000, and 5% of the years, Y=$15,000.
a. Calculate the mean and standard deviation of the damage in any year.
b. Consider an 'insurance pool' of 100 sufficiently dispersed homes, which implies the damage to dissimilar homes can be viewed as separately distributed as random variables. If ? is the average damage to those 100 homes in a year, (i) what is the expected value of the average damage? (ii) What is the probability that ? exceeds $2000?
Explain the difference among the usual (product moment) correlation and rank correlation. In what situations is it more appropriate to use rank correlation?
DISCUSS THE CENTRAL ECONOMIC PROBLEM FACING THIS GROUP OF SURVIVORS
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Problem: a) In what circumstances would you apply switching models? b) Using dummy variables for seasonality show how you would test for January effects in financial data?
(b) Suppose that the initial conditions are as follows: y0 = 0 and et = 0 for t= 0. Impose the initial conditions in order to find the general solution.
Peter's utility function is u(x, y) = x + 2y where x is the number of ounces of coffee and y is the quantity of sugar in grams. Let unit prices be given by P x = 6 cents, P
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